ihdp {bartcs} | R Documentation |

## Infant Health and Development Program Data

### Description

Infant Health and Development Program (IHDP) is a randomized experiment from
1985 to 1988 which studied the effect of home visits on cognitive test scores
for infants.

### Usage

```
ihdp
```

### Format

- treatment
Given treatment.

- y_factual
Observed outcome.

- y_cfactual
Potential outcome given the opposite treatment.

- mu0
Control conditional means.

- mu1
Treated conditional means.

- X1 ~ X6
Confounders with continuous values.

- X7 ~ X25
Confounders with binary values.

### Details

This dataset was first used by Hill (2011), then used by other researchers
(Shalit et al. 2017, Louizos et al. 2017).

### Source

Our version of dataset is the dataset used by Louizos et al. (2017).
This is the first realization of 10 generated datasets and you can find
other realizations from
https://github.com/AMLab-Amsterdam/CEVAE.

### References

Hill, J. L. (2011). Bayesian nonparametric modeling for causal inference.
*Journal of Computational and Graphical Statistics*, 20(1), 217-240.
doi:10.1198/jcgs.2010.08162

Louizos, C., Shalit, U., Mooij, J. M., Sontag, D., Zemel, R., & Welling, M. (2017).
Causal effect inference with deep latent-variable models.
*Advances in neural information processing systems*, 30.
doi:10.48550/arXiv.1705.08821
https://github.com/AMLab-Amsterdam/CEVAE

Shalit, U., Johansson, F. D., & Sontag, D. (2017, July).
Estimating individual treatment effect: generalization bounds and algorithms.
In *International Conference on Machine Learning* (pp. 3076-3085). PMLR.
doi:10.48550/arXiv.1606.03976

[Package

*bartcs* version 1.2.0

Index]